Chaos-based audio encryption algorithm using biometric image and SHA-256 hash algorithm

Today, Internet users who share personal and professional data are concerned about the safety of the data. Encryption is one way to safeguard sensitive and private data on internet sites. Encrypting audio data is more challenging than other types of data owing to the correlation between neighbouring samples. Encryption algorithms based on chaos theory are now widely used to protect digital audio and image data. Chaos theory is the idea that tiny changes in initial conditions will escalate into much more significant difference in the future. This paper proposes a robust and effective method for audio encryption based on chaos theory and user-biometric images. In addition, the SHA-256 hash technique and zigzag traversal are employed to bolster the system. First, the algorithm reads the sample values from the input audio and then separates them into byte blocks. In addition, each byte block is blended with chaotic sequences generated by the Henon map first, then by the Lorenz system. The chaotic sequences generated by the logistic map are used to create different initial values for the Henon map and Lorenz Systems. The initial values of the logistic map are constructed using the hash values of the plain audio signals and biometric images produced by the SHA-256 hash algorithm. The proposed method has a variety of desirable characteristics, such as good chaotic behaviour, low computational complexity, a huge key space, and substantial parameter space. The results of the various security and performance assessments show that the proposed algorithm is more robust and efficient than existing approaches against all forms of crypto-graphic threats.